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MIT researchers have developed a type of neural network that learns on the job, not just during its training phase. These flexible algorithms, dubbed “liquid” networks, change their underlying equations to continuously adapt to new data inputs. The advance could aid decision making based on data streams that change over time, including those involved in medical diagnosis and autonomous driving.

https://news.mit.edu/2021/machine-learning-adapts-0128?fbclid=IwAR0aSxljQkBPobnsHpmQN8DHc2bjQ6LK4ntfXYTseNnPrbBgkbEYRriAAek

“Liquid” machine-learning system adapts to changing conditions MIT researchers developed a neural network that learns on the job, not just during training. The “liquid” network varies its equations’ parameters, enhancing its ability to analyze time series data. The advance could boost autonomous driving, medical diagnosis, and more.

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